Ordered weighted average based grouping of nanomaterials with Arsinh and dose response similarity models

In the context of the EU GRACIOUS project, we propose a novel procedure for similarity assessment and grouping of nanomaterials. This methodology is based on the (1) Arsinh transformation function for scalar properties, (2) full curve shape comparison by application of a modified Kolmogorov-Smirnov metric for bivariate properties, (3) Ordered Weighted Average (OWA) aggregation-based grouping distance, and (4) hierarchical clustering. The approach allows for grouping of nanomaterials that is not affected by the dataset, so that group membership will not change when new candidates are included in the set of assessed materials. To facilitate the application of the proposed methodology, a software script was developed by using the R programming language which is currently under migration to a web tool. The presented approach was tested against a dataset, derived from literature review, related to immobilization of Daphnia magna and reporting information on several nanomaterials and properties.

Bayesian based similarity assessment of nanomaterials to inform grouping

Nanoforms can be manufactured in plenty of variants by differing their physicochemical properties and toxicokinetic behaviour which can affect their hazard potential. To avoid testing of each single nanomaterial and nanoform variation and subsequently save resources, grouping and read-across strategies are used to estimate groups of substances, based on carefully selected evidence, that could potentially have similar human health and environmental hazard impact. A novel computational similarity method is presented aiming to compare dose-response curves and identify sets of similar nanoforms. The suggested method estimates the statistical model that best fits the data by leveraging pairwise Bayes Factor analysis to compare pairs of curves and evaluate whether each of the nanoforms is sufficiently similar to all other nanoforms. Pairwise comparisons to benchmark materials are used to define threshold similarity values and set the criteria for identifying groups of nanoforms with comparatively similar toxicity. Applications to use case data are shown to demonstrate that the method can support grouping hypotheses linked to a certain hazard endpoint and route of exposure.

Occupational risk of nano-biomaterials: Assessment of nano-enabled magnetite contrast agent using the BIORIMA Decision Support System

The assessment of the safety of nano-biomedical products for patients is an essential prerequisite for their market authorization. However, it is also required to ensure the safety of the workers who may be unintentionally exposed to the nano-biomaterials (NBMs) in these medical applications during their synthesis, formulation into products and end-of-life processing and also of the medical professionals (e.g., nurses, doctors, dentists) using the products for treating patients. There is only a handful of workplace risk assessments focussing on NBMs used in medical applications. Our goal is to contribute to increasing the knowledge in this area by assessing the occupational risks of magnetite (Fe₃O₄) nanoparticles coated with PLGA-b-PEG-COOH used as contrast agent in magnetic resonance imaging (MRI) by applying the software-based Decision Support System (DSS) which was developed in the EU H2020 project BIORIMA. The occupational risk assessment was performed according to regulatory requirements and using state-of-the-art models for hazard and exposure assessment, which are part of the DSS. Exposure scenarios for each life cycle stage were developed using data from literature, inputs from partnering industries and results of a questionnaire distributed to healthcare professionals, i.e., physicians, nurses, technicians working with contrast agents for MRI. Exposure concentrations were obtained either from predictive exposure models or monitoring campaigns designed specifically for this study. Derived No-Effect Levels (DNELs) were calculated by means of the APROBA tool starting from in vivo hazard data from literature. The exposure estimates/measurements and the DNELs were used to perform probabilistic risk characterisation for the formulated exposure scenarios, including uncertainty analysis. The obtained results revealed negligible risks for workers along the life cycle of magnetite NBMs used as contrast agent for the diagnosis of tumour cells in all exposure scenarios except in one when risk is considered acceptable after the adoption of specific risk management measures. The study also demonstrated the added value of using the BIORIMA DSS for quantification and communication of occupational risks of nano-biomedical applications and the associated uncertainties.

How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity

The risk of each nanoform (NF) of the same substance cannot be assumed to be the same, as they may vary in their physicochemical characteristics, exposure and hazard. However, neither can we justify a need for more animal testing and resources to test every NF individually. To reduce the need to test all NFs, (regulatory) information requirements may be fulfilled by grouping approaches. For such grouping to be acceptable, it is important to demonstrate similarities in physicochemical properties, toxicokinetic behaviour, and (eco)toxicological behaviour. The GRACIOUS Framework supports the grouping of NFs, by identifying suitable grouping hypotheses that describe the key similarities between different NFs. The Framework then supports the user to gather the evidence required to test these hypotheses and to subsequently assess the similarity of the NFs within the proposed group. The evidence needed to support a hypothesis is gathered by an Integrated Approach to Testing and Assessment (IATA), designed as decision trees constructed of decision nodes. Each decision node asks the questions and provides the methods needed to obtain the most relevant information. This White paper outlines existing and novel methods to assess similarity of the data generated for each decision node, either via a pairwise analysis conducted property-by-property, or by assessing multiple decision nodes simultaneously via a multidimensional analysis. For the pairwise comparison conducted property-by-property we included in this White paper: The x-fold, Bayesian and Arsinh-OWA distance algorithms performed comparably in the scoring of similarity between NF pairs. The Euclidean distance was also useful, but only with proper data transformation. The x-fold method does not standardize data, and thus produces skewed histograms, but has the advantage that it can be implemented without programming knowhow. A range of multidimensional evaluations, using for example dendrogram clustering approaches, were also investigated. Multidimensional distance metrics were demonstrated to be difficult to use in a regulatory context, but from a scientific perspective were found to offer unexpected insights into the overall similarity of very different materials. In conclusion, for regulatory purposes, a property-by-property evaluation of the data matrix is recommended to substantiate grouping, while the multidimensional approaches are considered to be tools of discovery rather than regulatory methods.

A Weight of Evidence approach to classify nanomaterials according to the EU Classification, Labelling and Packaging Regulation criteria

In the context of the European Union (EU) Horizon 2020 GRACIOUS project (Grouping, Read-Across, Characterisation and classification framework for regulatory risk assessment of manufactured nanomaterials and Safer design of nano-enabled products), we proposed a quantitative Weight of Evidence (WoE) approach for hazard classification of nanomaterials (NMs). This approach is based on the requirements of the European Regulation on Classification, Labelling and Packaging of Substances and Mixtures (the CLP regulation), which implements the United Nations' Globally Harmonized System of Classification and Labelling of Chemicals (UN GHS) in the European Union. The goal of this WoE methodology is to facilitate classification of NMs according to CLP criteria, following the decision trees defined in ECHA's CLP regulatory guidance. In the WoE, results from heterogeneous studies are weighted according to data quality and completeness criteria, integrated, and then evaluated by expert judgment to obtain a hazard classification, resulting in a coherent and justifiable methodology. Moreover, the probabilistic nature of the proposed approach enables highlighting the uncertainty in the analysis. The proposed methodology involves the following stages: (1) collection of data for different NMs related to the endpoint of interest: each study related to each NM is referred as a Line of Evidence (LoE); (2) computation of weighted scores for each LoE: each LoE is weighted by a score calculated based on data quality and completeness criteria defined in the GRACIOUS project; (3) comparison and integration of the weighed LoEs for each NM: A Monte Carlo resampling approach is adopted to quantitatively and probabilistically integrate the weighted evidence; and (4) assignment of each NM to a hazard class: according to the results, each NM is assigned to one of the classes defined by the CLP regulation. Furthermore, to facilitate the integration and the classification of the weighted LoEs, an online R tool was developed. Finally, the approach was tested against an endpoint relevant to CLP (Aquatic Toxicity) using data retrieved from the eNanoMapper database, results obtained were consistent to results in REACH registration dossiers and in recent literature.

Risk Management Framework for Nano-Biomaterials Used in Medical Devices and Advanced Therapy Medicinal Products

The convergence of nanotechnology and biotechnology has led to substantial advancements in nano-biomaterials (NBMs) used in medical devices (MD) and advanced therapy medicinal products (ATMP). However, there are concerns that applications of NBMs for medical diagnostics, therapeutics and regenerative medicine could also pose health and/or environmental risks since the current understanding of their safety is incomplete. A scientific strategy is therefore needed to assess all risks emerging along the life cycles of these products. To address this need, an overarching risk management framework (RMF) for NBMs used in MD and ATMP is presented in this paper, as a result of a collaborative effort of a team of experts within the EU Project BIORIMA and with relevant inputs from external stakeholders. The framework, in line with current regulatory requirements, is designed according to state-of-the-art approaches to risk assessment and management of both nanomaterials and biomaterials. The collection/generation of data for NBMs safety assessment is based on innovative integrated approaches to testing and assessment (IATA). The framework can support stakeholders (e.g., manufacturers, regulators, consultants) in systematically assessing not only patient safety but also occupational (including healthcare workers) and environmental risks along the life cycle of MD and ATMP. The outputs of the framework enable the user to identify suitable safe(r)-by-design alternatives and/or risk management measures and to compare the risks of NBMs to their (clinical) benefits, based on efficacy, quality and cost criteria, in order to inform robust risk management decision-making.

Comparison of species sensitivity distribution modeling approaches for environmental risk assessment of nanomaterials - A case study for silver and titanium dioxide representative materials

Species sensitivity distributions (SSDs) are used in chemical safety assessments to derive predicted-no-effect-concentrations (PNECs) for substances with a sufficient amount of relevant and reliable ecotoxicity data available. For engineered nanomaterials (ENMs), ecotoxicity data are often compromised by poor reproducibility and the lack of nano-specific characterization needed describe an ENM under test exposure conditions. This may influence the outcome of SSD modelling and hence the regulatory decision-making. This study investigates how the outcome of SSD modelling is influenced by: 1) Selecting input data based on the nano-specific "nanoCRED" reliability criteria, 2) Direct SSD modelling avoiding extrapolation of data by including long-term/chronic NOECs only, and 3) Weighting data according to their nano-specific quality, the number of data available for each species, and the trophic level abundance in the ecosystem. Endpoints from freshwater ecotoxicity studies were collected for the representative nanomaterials NM-300 K (silver) and NM-105 (titanium dioxide), evaluated for regulatory reliability and scored according to the level of nano-specific characterization conducted. The compiled datasets are unique in exclusively dealing with representative ENMs showing minimal batch-to-batch variation. The majority of studies were evaluated as regulatory reliable, while the degree of nano-specific characterization varied greatly. The datasets for NM-300 K and NM-105 were used as input to the nano-weighted n-SSWD model, the probabilistic PSSD+, and the conventional SSD Generator by the US EPA. The conventional SSD generally yielded the most conservative, but least precise HC₅ values, with 95 % confidence intervals up to 100-fold wider than the other models. The inclusion of regulatory reliable data only, had little effect on the HC₅ generated by the conventional SSD and the PSSD+, whereas the n-SSWD estimated different HC₅ values based on data segregated according to reliability, especially for NM-105. The n-SSWD weighting of data significantly affected the estimated HC₅ values, however in different ways for the sub-datasets of NM-300 K and NM-105. For NM-300 K, the inclusion of NOECs only in the weighted n-SSWD yielded the most conservative HC₅ of all datasets and models (a HC₅ based on NOECs only could not be estimated for NM-105, due to limited number of data). Overall, the estimated HC₅ values of all models are within a relatively limited concentration range of 25-100 ng Ag/L for NM-300 K and 1-15 μgTiO₂/L for NM-105.

Use of multiple indicators to compare sustainability performance of organic vs conventional vineyard management

The wine sector is paying more attention to sustainable wine production practices, but this topic is highly debated because organic viticulture aims to a reduction of environmental impacts, while conventional viticulture ensures an increase of yield. This work provides an economic and environmental comparison using different indicators whereas no previous studies on viticulture have faced on both aspects of sustainability. Two distinct vineyards within the same case study farm were considered, where conventional and organic viticulture practices were applied for 5 years. For each type of production, we calculated the economic benefit and environmental indicators such as the Water Footprint, Carbon Footprint, and an indicator of environmental performance associated with the vineyard phase ("Vineyard Management" or "Vigneto" indicator part of the Italian VIVA certification framework). This latter considers six sub-indicators investigating pesticides management, fertilizers management, organic matter content, soil compaction, soil erosion, and landscape quality. The multi criteria approach is a novel framework assessing sustainability on vineyard management using environmental indicators from VIVA calculator and the economic aspect. Main results showed that organic management in viticulture can be applied without having economic losses and with the benefit of better preserving the natural capital.

Controlling the risks of nano-enabled products through the life cycle: The case of nano copper oxide paint for wood protection and nano-pigments used in the automotive industry

The widespread use of engineered nanomaterials (ENMs) in consumer products and the overwhelming uncertainties in their ecological and human health risks have raised concerns regarding their safety among industries and regulators. There has been an ongoing debate over the past few decades on ways to overcome the challenges in assessing and mitigating nano-related risks, which has reached a phase of general consensus that nanotechnology innovation should be accompanied by the application of the precautionary principle and best practice risk management, even if the risk assessment uncertainties are large. We propose a quantitative methodology for selecting the optimal risk control strategy based on information about human health and ecological risks, efficacy of risk mitigation measures, cost and other contextual factors. The risk control (RC) methodology was developed in the European FP7 research project SUN and successfully demonstrated in two case studies involving real industrial nano-enabled products (NEPs): nano-scale copper oxide (CuO) and basic copper carbonate (Cu₂(OH)₂CO₃) used as antimicrobial and antifungal coatings and impregnations for the preservation of treated wood, and two nanoscale pigments used for colouring plastic automotive parts (i.e. red organic pigment and carbon black). The application of RC for human health risks showed that although nano-related risks could easily be controlled in automotive plastics case study with modifications in production technology or specific type of engineering controls, nano-related risks due to sanding and sawing copper oxide painted wood were non-acceptable in the use lifecycle stage and would need the identification of a more effective risk control strategy.

Comparison of Water-focused Life Cycle Assessment and Water Footprint Assessment: The case of an Italian wine

In recent decades, the debate on how to implement and measure sustainability in food production gained increasing importance and interest for agriculture. In the wine sector, producers are increasingly pursuing sustainable practices, including measures for water preservation from degradation and overuse. But methodologies for assessing and communicating the impacts on water resources need to be understood in detail to guide the selection of the most appropriate management practices, support environmental labelling and promote environmental-friendly products to consumers. This work focuses on the impacts on water resources associated with the production of Italian wine by comparing two methodologies: the Water-focused Life Cycle Assessment and the "Water" indicator included in the Italian "VIVA" certification framework, which is based on the Water Footprint Assessment. The two methodologies address the impact on freshwater consumption and degradation from a life cycle perspective. VIVA is based on a water balance method that reflects a volumetric measure of water consumption, while the LCA-based approach investigates both the freshwater consumption and depletion using different impact indicators. The study goal is to compare the two methodologies to understand how their outcomes can support and improve the management of water-related issues in wine production. One main conclusion is that the WATER indicator within VIVA framework can provide more precise recommendations for the optimal management of water use during the vineyard phase, while LCA approach highlights impact hotspots related to both direct and indirect use of water resources (e.g., it points out the relevant contribution of the bottling stage to different impact indicators). The comparative application of both methodologies can provide useful insights into the water-related impacts of different wine production processes and stages and support a comprehensive assessment of the best management practices, unless the differences in the methodological approaches and goals are well understood by assessors.

"AMORE" Decision Support System for probabilistic Ecological Risk Assessment - Part II: Effect assessment of the case study on cyanide

Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability and relevance of available data for analysing their possible use in the aforementioned processes. In this context, a new methodology which has been developed based on Multi-Criteria Decision Analysis (MCDA) techniques, is being used, demonstrated and tested for analysing the reliability and relevance of ecotoxicological data of cyanide (which are produced through laboratory biotests for individual effects). The proposed methodology is also used for the production of Weighted by Data Quality Species Sensitivity Distributions (SSD-WDQ), as a component of the Ecological Risk Assessment of chemicals in aquatic systems. The SSD-WDQ production resulted in the estimation of environmental quality criteria (hazard concentration affecting 5% and 50% of the species). The proposed work is part of the development of the AMORE Decision Support System (DSS) for the application of probabilistic Ecological Risk Assessment (ERA), presented in the companion paper (Isigonis et al., 2019). The DSS has been tested through a case study on ERA of cyanide in the watershed of river Selune in France. The paper presents the 'Effect Assessment' of cyanide, based on the aforementioned methodologies. The main results presented in the paper are the probabilistic analysis of the estimated species sensitivity on cyanide (Effect Assessment) and the calculation of Hazardous Concentration (HCx) of the same contaminant in the Selune river area, based on the functionalities of the DSS. The results are described and discussed in detail, with the use of various graphs and indices. The indices are calculated for all the available ecotoxicological data, as well as for the data on trophic levels or taxonomic groups separately. An effect comparison is presented between the innovative methodologies included in the DSS and the currently existing methodologies.

"AMORE" Decision Support System for probabilistic Ecological Risk Assessment - Part I: Exposure and risk assessment of the case study on cyanide

Ecological Risk Assessment of chemicals in fluvial systems is a highly researched topic, but its importance for the environmental protection of our planet is vital. Thus, new developments and improvements to existing methodologies are proposed constantly, for providing more advanced tools and more accurate results to researchers and other interested parties. In the field of probabilistic Ecological Risk Assessment, a new Decision Support System is proposed, developed, tested and evaluated. The AMORE DSS is a modular DSS, which incorporates a series of new methodologies, and is built upon the notions of 'Exposure Assessment', 'Effect Assessment' and 'Risk Assessment'. The AMORE Decision Support System has been developed as part of the AMORE research project (French National Research Agency project). The DSS provides a set of tools for analysing and integrating both exposure and effect information in order to evaluate the risk for species living on a given contaminated aquatic system in terms of the Potentially Affected Fraction. The DSS has been tested through a case study on ERA of cyanide in the watershed of river Selune in France. The paper presents the 'Exposure Assessment' and 'Risk Assessment' of the cyanide case study, as well as the complete functionalities of the AMORE DSS. The main results presented in the paper are the statistical analysis of the measured environmental concentrations of cyanide (Exposure Assessment) and the probabilistic 'Risk assessment' of the same contaminant in the area of interest, based on the functionalities of the DSS. The results are described and discussed in detail with the use of various graphs and risk indices. The risk indices are calculated for all the available ecotoxicological data, as well as for the data on trophic levels or taxonomic groups separately. A risk comparison is presented between the innovative methodologies included in the DSS and the currently existing methodologies.

An Information System for Brownfield Regeneration: providing customised information according to stakeholders' characteristics and needs

In the EU brownfield presence is still considered a widespread problem. Even though, in the last decades, many research projects and initiatives developed a wealth of methods, guidelines, tools and technologies aimed at supporting brownfield regeneration. However, this variety of products had and still has a limited practical impact on brownfield revitalisation success, because they are not used in their entire potential due to their scarce visibility. Also, another problem that stakeholders face is finding customised information. To overcome this non-visibility and not-sufficient customisation of information, the Information System for Brownfield Regeneration (ISBR) has been developed, based on Artificial Neural Networks, which allows understanding stakeholders' information needs by providing tailored information. The ISBR has been tested by stakeholders from the EU project TIMBRE case studies, located in the Czech Republic, Germany, Poland and Romania. Data gained during tests allowed to understand stakeholders' information needs. Overall, stakeholders showed to be concerned first on remediation aspects, then on benchmarking information, which are valuable to improve practices in the complex field of brownfield regeneration, and then on the relatively new issue of sustainability applied to brownfield regeneration and remediation. Mature markets confirmed their interest for remediation-related aspects, highlighting the central role that risk assessment plays in the process. Emerging markets showed to seek information and tools for strategic and planning issues, like brownfield inventories and georeferenced data sets. Results led to conclude that a new improved platform, combining the ISBR functionalities with geo-referenced ones, would be useful and could represent a further research application.

Quantitative human health risk assessment along the lifecycle of nano-scale copper-based wood preservatives

The use of nano-scale copper oxide (CuO) and basic copper carbonate (Cu₂(OH)₂CO₃) in both ionic and micronized wood preservatives has raised concerns about the potential of these substances to cause adverse humans health effects. To address these concerns, we performed quantitative (probabilistic) human health risk assessment (HHRA) along the lifecycles of these formulations used in antibacterial and antifungal wood coatings and impregnations by means of the EU FP7 SUN project's Decision Support System (SUNDS, www.sunds.gd). The results from the risk analysis revealed inhalation risks from CuO in exposure scenarios involving workers handling dry powders and performing sanding operations as well as potential ingestion risks for children exposed to nano Cu₂(OH)₂CO₃ in a scenario involving hand-to-mouth transfer of the substance released from impregnated wood. There are, however, substantial uncertainties in these results, so some of the identified risks may stem from the safety margin of extrapolation to fill data gaps and might be resolved by additional testing. Our stochastic approach successfully communicated the contribution of different sources of uncertainty in the risk assessment. The main source of uncertainty was the extrapolation from short to long-term exposure, which was necessary due to the lack of (sub)chronic in vivo studies with CuO and Cu₂(OH)₂CO₃. Considerable uncertainties also stemmed from the use of default inter- and intra-species extrapolation factors.

Probabilistic risk assessment of emerging materials: case study of titanium dioxide nanoparticles

The development and use of emerging technologies such as nanomaterials can provide both benefits and risks to society. Emerging materials may promise to bring many technological advantages but may not be well characterized in terms of their production volumes, magnitude of emissions, behaviour in the environment and effects on living organisms. This uncertainty can present challenges to scientists developing these materials and persons responsible for defining and measuring their adverse impacts. Human health risk assessment is a method of identifying the intrinsic hazard of and quantifying the dose-response relationship and exposure to a chemical, to finally determine the estimation of risk. Commonly applied deterministic approaches may not sufficiently estimate and communicate the likelihood of risks from emerging technologies whose uncertainty is large. Probabilistic approaches allow for parameters in the risk assessment process to be defined by distributions instead of single deterministic values whose uncertainty could undermine the value of the assessment. A probabilistic approach was applied to the dose-response and exposure assessment of a case study involving the production of nanoparticles of titanium dioxide in seven different exposure scenarios. Only one exposure scenario showed a statistically significant level of risk. In the latter case, this involved dumping high volumes of nano-TiO₂ powders into an open vessel with no personal protection equipment. The probabilistic approach not only provided the likelihood of but also the major contributing factors to the estimated risk (e.g. emission potential).

Probabilistic approach for assessing infants' health risks due to ingestion of nanoscale silver released from consumer products

Silver nanoparticles (n-Ag) are widely used in consumer products and many medical applications because of their unique antibacterial properties. Their use is raising concern about potential human exposures and health effects. Therefore, it is informative to assess the potential human health risks of n-Ag in order to ensure that nanotechnology-based consumer products are deployed in a safe and sustainable way. Even though toxicity studies clearly show the potential hazard of n-Ag, there have been few attempts to integrate hazard and exposure assessments to evaluate risks. The underlying reason for this is the difficulty in characterizing exposure and the lack of toxicity studies essential for human health risk assessment (HHRA). Such data gaps introduce significant uncertainty into the risk assessment process. This study uses probabilistic methods to assess the relative uncertainty and potential risks of n-Ag exposure to infants. In this paper, we estimate the risks for infants potentially exposed to n-Ag through drinking juice or milk from sippy cups or licking baby blankets containing n-Ag. We explicitly evaluate uncertainty and variability contained in available dose-response and exposure data in order to make the risk characterization process transparent. Our results showed that individual margin of exposures for oral exposure to sippy cups and baby blankets containing n-Ag exhibited minimal risk.

Targeted selection of brownfields from portfolios for sustainable regeneration: User experiences from five cases testing the Timbre Brownfield Prioritization Tool

Prioritizing brownfields for redevelopment in real estate portfolios can contribute to more sustainable regeneration and land management. Owners of large real estate and brownfield portfolios are challenged to allocate their limited resources to the development of the most critical or promising sites, in terms of time and cost efficiency. Authorities worried about the negative impacts of brownfields - in particular in the case of potential contamination - on the environment and society also need to prioritize their resources to those brownfields that most urgently deserve attention and intervention. Yet, numerous factors have to be considered for prioritizing actions, in particular when adhering to sustainability principles. Several multiple-criteria decision analysis (MCDA) approaches and tools have been suggested in order to support these actors in managing their brownfield portfolios. Based on lessons learned from the literature on success factors, sustainability assessment and MCDA approaches, researchers from a recent EU project have developed the web-based Timbre Brownfield Prioritization Tool (TBPT). It facilitates assessment and prioritization of a portfolio of sites on the basis of the probability of successful and sustainable regeneration or according to individually specified objectives. This paper introduces the challenges of brownfield portfolio management in general and reports about the application of the TBPT in five cases: practical test-uses by two large institutional land owners from Germany, a local and a regional administrative body from the Czech Republic, and an expert from a national environmental authority from Romania. Based on literature requirements for sustainability assessment tools and on the end-users' feedbacks from the practical tests, we discuss the TBPT's strengths and weaknesses in order to inform and give recommendations for future development of prioritization tools.

Climate change impacts on marine water quality: The case study of the Northern Adriatic sea

Climate change is posing additional pressures on coastal ecosystems due to variations in water biogeochemical and physico-chemical parameters (e.g., pH, salinity) leading to aquatic ecosystem degradation. With the main aim of analyzing the potential impacts of climate change on marine water quality, a Regional Risk Assessment methodology was developed and applied to coastal marine waters of the North Adriatic. It integrates the outputs of regional biogeochemical and physico-chemical models considering future climate change scenarios (i.e., years 2070 and 2100) with site-specific environmental and socio-economic indicators. Results showed that salinity and temperature will be the main drivers of changes, together with macronutrients, especially in the area of the Po' river delta. The final outputs are exposure, susceptibility and risk maps supporting the communication of the potential consequences of climate change on water quality to decision makers and stakeholders and provide a basis for the definition of adaptation and management strategies.

Timbre Brownfield Prioritization Tool to support effective brownfield regeneration

In the last decade, the regeneration of derelict or underused sites, fully or partly located in urban areas (or so called "brownfields"), has become more common, since free developable land (or so called "greenfields") has more and more become a scare and, hence, more expensive resource, especially in densely populated areas. Although the regeneration of brownfield sites can offer development potentials, the complexity of these sites requires considerable efforts to successfully complete their revitalization projects and the proper selection of promising sites is a pre-requisite to efficiently allocate the limited financial resources. The identification and analysis of success factors for brownfield sites regeneration can support investors and decision makers in selecting those sites which are the most advantageous for successful regeneration. The objective of this paper is to present the Timbre Brownfield Prioritization Tool (TBPT), developed as a web-based solution to assist stakeholders responsible for wider territories or clusters of brownfield sites (portfolios) to identify which brownfield sites should be preferably considered for redevelopment or further investigation. The prioritization approach is based on a set of success factors properly identified through a systematic stakeholder engagement procedure. Within the TBPT these success factors are integrated by means of a Multi Criteria Decision Analysis (MCDA) methodology, which includes stakeholders' requalification objectives and perspectives related to the brownfield regeneration process and takes into account the three pillars of sustainability (economic, social and environmental dimensions). The tool has been applied to the South Moravia case study (Czech Republic), considering two different requalification objectives identified by local stakeholders, namely the selection of suitable locations for the development of a shopping centre and a solar power plant, respectively. The application of the TBPT to the case study showed that it is flexible and easy to adapt to different local contexts, allowing the assessors to introduce locally relevant parameters identified according to their expertise and considering the availability of local data.

A Multi-Criteria Decision Analysis based methodology for quantitatively scoring the reliability and relevance of ecotoxicological data

Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability of available data for analysing their possible use in the aforementioned processes. The thorough analysis of currently available frameworks for the assessment of ecotoxicological data has led to the identification of significant flaws but at the same time various opportunities for improvement. In this context, a new methodology, based on Multi-Criteria Decision Analysis (MCDA) techniques, has been developed with the aim of analysing the reliability and relevance of ecotoxicological data (which are produced through laboratory biotests for individual effects), in a transparent quantitative way, through the use of expert knowledge, multiple criteria and fuzzy logic. The proposed methodology can be used for the production of weighted Species Sensitivity Weighted Distributions (SSWD), as a component of the ecological risk assessment of chemicals in aquatic systems. The MCDA aggregation methodology is described in detail and demonstrated through examples in the article and the hierarchically structured framework that is used for the evaluation and classification of ecotoxicological data is shortly discussed. The methodology is demonstrated for the aquatic compartment but it can be easily tailored to other environmental compartments (soil, air, sediments).

Species sensitivity weighted distribution for ecological risk assessment of engineered nanomaterials: the n-TiO2 case study

Societal concerns about the environmental risks of engineered nanomaterials (ENMs) have recently increased, but nano-ecological risk assessments are constrained by significant gaps in basic information on long-term effects and exposures, for example. An approach to the ecological risk assessment of ENMs is proposed that can operate in the context of high uncertainty. This approach further develops species sensitivity weighted distribution (SSWD) by including 3 weighting criteria (species relevance, trophic level abundance, and nanotoxicity data quality) to address nano-specific needs (n-SSWD). The application of n-SSWD is illustrated for nanoscale titanium dioxide (n-TiO2 ), which is available in different crystal forms; it was selected because of its widespread use in consumer products (e.g., cosmetics) and the ample availability of data from ecotoxicological studies in the literature (including endpoints for algae, invertebrates, bacteria, and vertebrates in freshwater, saltwater, and terrestrial compartments). The n-SSWD application resulted in estimation of environmental quality criteria (hazard concentration affecting 5% and 50% of the species) and ecological risk (potentially affected fraction of species), which were then compared with similar results obtained by applying the traditional species sensitivity distribution (SSD) approach to the same dataset. The n-SSWDs were also built for specific trophic levels (e.g., primary producers) and taxonomic groups (e.g., algae), which helped to identify the most sensitive organisms. These results showd that n-SSWD is a valuable risk tool, although further testing is suggested.

Ecological status classification of the Taizi River Basin, China: a comparison of integrated risk assessment approaches

Integrated risk assessment approaches allow to achieve a sound evaluation of ecological status of river basins and to gain knowledge about the likely causes of impairment, useful for informing and supporting the decision-making process. In this paper, the integrated risk assessment (IRA) methodology developed in the EU MODELKEY project (and implemented in the MODELKEY Decision Support System) is applied to the Taizi River (China), in order to assess its Ecological and Chemical Status according to EU Water Framework Directive (WFD) requirements. The available dataset is derived by an extensive survey carried out in 2009 and 2010 across the Taizi River catchment, including the monitoring of physico-chemical (i.e. DO, EC, NH3-_N, chemical oxygen demand (COD), biological oxygen demand in 5 days (BOD5) and TP), chemical (i.e. polycyclic aromatic hydrocarbons (PAHs) and metals), biological (i.e. macroinvertebrates, fish, and algae), and hydromorphological parameters (i.e. water quantity, channel change and morphology diversity). The results show a negative trend in the ecological status from the highland to the lowland of the Taizi River Basin. Organic pollution from agriculture and domestic sources (i.e. COD and BOD5), unstable hydrological regime (i.e. water quantity shortage) and chemical pollutants from industry (i.e. PAHs and metals) are found to be the main stressors impacting the ecological status of the Taizi River Basin. The comparison between the results of the IRA methodology and those of a previous study (Leigh et al. 2012) indicates that the selection of indicators and integrating methodologies can have a relevant impact on the classification of the ecological status. The IRA methodology, which integrates information from five lines of evidence (i.e., biology, physico-chemistry, chemistry, ecotoxicology and hydromorphology) required by WFD, allows to better identify the biological communities that are potentially at risk and the stressors that are most likely responsible for the observed alterations. This knowledge can be beneficial for a more effective restoration and management of the river basin ecosystem.

Risk-based prioritization methodology for the classification of groundwater pollution sources

Water management is one of the EU environmental priorities and it is one of the most serious challenges that today's major cities are facing. The main European regulation for the protection of water resources is represented by the Water Framework Directive (WFD) and the Groundwater Directive (2006/118/EC) which require the identification, risk-based ranking and management of sources of pollution and the identification of those contamination sources that threaten the achievement of groundwater's good quality status. The aim of this paper is to present a new risk-based prioritization methodology to support the determination of a management strategy for the achievement of the good quality status of groundwater. The proposed methodology encompasses the following steps: 1) hazard analysis, 2) pathway analysis, 3) receptor vulnerability analysis and 4) relative risk estimation. Moreover, by integrating GIS functionalities and Multi Criteria Decision Analysis (MCDA) techniques, it allows to: i) deal with several sources and multiple impacted receptors within the area of concern; ii) identify different receptors' vulnerability levels according to specific groundwater uses; iii) assess the risks posed by all contamination sources in the area; and iv) provide a risk-based ranking of the contamination sources that can threaten the achievement of the groundwater good quality status. The application of the proposed framework to a well-known industrialized area located in the surroundings of Milan (Italy) is illustrated in order to demonstrate the effectiveness of the proposed framework in supporting the identification of intervention priorities. Among the 32 sources analyzed in the case study, three sources received the highest relevance score, due to the medium-high relative risks estimated for Chromium (VI) and Perchloroethylene. The case study application showed that the developed methodology is flexible and easy to adapt to different contexts, thanks to the possibility to introduce specific relevant parameters identified according to expert judgment and data availability.

A risk-based methodology for ranking environmental chemical stressors at the regional scale

A "Risk-based Tool for the Regional Ranking of Environmental Chemical Stressors" has been developed, aimed at supporting decision-makers in the identification of priority environmental contaminants, as well as priority areas, to be further assessed. The tool implements a methodology based on a quantitative Weight-of-Evidence approach, integrating three types of information, identified as "Lines-of-Evidence" (LoE), namely: LoE "Environmental Contamination" (including data on chemical contamination in environmental matrices in the region, thus providing information on potential population exposure), LoE "Intake" (including results from human biomonitoring studies, i.e. concentration of chemicals in human biological matrices, thus providing an integrated estimation of exposure) and LoE "Observed Effects" (including information on the incidence of adverse health outcomes associated with environmental exposure to chemicals). A Multi-Criteria Decision Analysis (MCDA) methodology based on fuzzy logic has been developed to support the integration of information related to these three LoEs for each chemical stressor. The tool allows one to rank chemical stressors at different spatial scales, such as at the regional level as well as within each sub-area (e.g., counties). Moreover, it supports the identification of priority sub-areas within the region, where environmental and health data suggest possible adverse health effects and thus more investigation efforts are needed. To evaluate the performance of this newly developed tool, a case-study in the Flemish region (north of Belgium) has been selected. In the case-study, data on soil contamination by metals and organic contaminants were integrated with data on exposure and effect biomarkers measured in adolescents within the framework of the human biomonitoring study performed by the Flemish Centre of Expertise on Environment and Health in the period 2002-2006. The case-study demonstrated the performance of the tool in integrating qualitative and quantitative data with expert judgement for the identification of priority contaminants and areas. The proposed approach proved to be flexible, allowing for the incorporation of individual decision-maker's preferences, and, at the same time, to be transparent since all assumptions and value attributions are traceable.

Application of a quantitative weight of evidence approach for ranking and prioritising occupational exposure scenarios for titanium dioxide and carbon nanomaterials

Substantial limitations and uncertainties hinder the exposure assessment of engineered nanomaterials (ENMs). The present deficit of reliable measurements and models will inevitably lead in the near term to qualitative and uncertain exposure estimations, which may fail to support adequate risk assessment and management. Therefore it is necessary to complement the current toolset with user-friendly methods for near-term nanosafety evaluation. This paper proposes an approach for relative exposure screening of ENMs. For the first time, an exposure model explicitly implements quantitative weight of evidence (WoE) methods and utilises expert judgement for filling data gaps in the available evidence-base. Application of the framework is illustrated for screening of exposure scenarios for nanoscale titanium dioxide, carbon nanotubes and fullerenes, but it is applicable to other nanomaterials as well. The results show that the WoE-based model overestimates exposure for scenarios where expert judgement was substantially used to fill data gaps, which suggests its conservative nature. In order to test how variations in input data influence the obtained results, probabilistic Monte Carlo sensitivity analysis was applied to demonstrate that the model performs in stable manner.

Climate change impact assessment in Veneto and Friuli Plain groundwater. Part II: a spatially resolved regional risk assessment

Climate change impact assessment on water resources has received high international attention over the last two decades, due to the observed global warming and its consequences at the global to local scale. In particular, climate-related risks for groundwater and related ecosystems pose a great concern to scientists and water authorities involved in the protection of these valuable resources. The close link of global warming with water cycle alterations encourages research to deepen current knowledge on relationships between climate trends and status of water systems, and to develop predictive tools for their sustainable management, copying with key principles of EU water policy. Within the European project Life+ TRUST (Tool for Regional-scale assessment of groundwater Storage improvement in adaptation to climaTe change), a Regional Risk Assessment (RRA) methodology was developed in order to identify impacts from climate change on groundwater and associated ecosystems (e.g. surface waters, agricultural areas, natural environments) and to rank areas and receptors at risk in the high and middle Veneto and Friuli Plain (Italy). Based on an integrated analysis of impacts, vulnerability and risks linked to climate change at the regional scale, a RRA framework complying with the Sources-Pathway-Receptor-Consequence (SPRC) approach was defined. Relevant impacts on groundwater and surface waters (i.e. groundwater level variations, changes in nitrate infiltration processes, changes in water availability for irrigation) were selected and analyzed through hazard scenario, exposure, susceptibility and risk assessment. The RRA methodology used hazard scenarios constructed through global and high resolution model simulations for the 2071-2100 period, according to IPCC A1B emission scenario in order to produce useful indications for future risk prioritization and to support the addressing of adaptation measures, primarily Managed Artificial Recharge (MAR) techniques. Relevant outcomes from the described RRA application highlighted that potential climate change impacts will occur with different extension and magnitude in the case study area. Particularly, qualitative and quantitative impacts on groundwater will occur with more severe consequences in the wettest and in the driest scenario (respectively). Moreover, such impacts will likely have little direct effects on related ecosystems - croplands, forests and natural environments - lying along the spring area (about 12% of croplands and 2% of natural environments at risk) while more severe consequences will indirectly occur on natural and anthropic systems through the reduction in quality and quantity of water availability for agricultural and other uses (about 80% of agricultural areas and 27% of groundwater bodies at risk).

Regional risk assessment for contaminated sites part 3: spatial decision support system

Large scale (e.g. regional or national) assessments of contaminated sites may be very costly in terms of investigation and methodological (i.e. risk assessment procedures) requirements and may produce a quantity of information that usually discourages examination by decision-makers. Moreover, most of the existing tools effectively support local environmental risk assessment and management, but lack the capabilities of larger scale analysis, not mentioning the absence of the relevant component of socio-economic prioritization. To respond to the concerns and the management needs of experts and decision makers, the Spatial decision support sYstem for Regional rIsk Assessment of Degraded land (SYRIADE DSS) was developed and is presented according to its three modules: Regional Risk Assessment, Socio-economic Assessment and Integrated Assessment, respectively. The system allows to rank potentially contaminated sites for priority of investigation, when no information on characterization and risk by site specific methodologies is available. This GIS-based system embeds an innovative spatial and relative risk assessment procedure, and proposes the integrated analysis of different data (environmental and socio-economic) for the concerned sites, eliciting when necessary experts' knowledge and stakeholders' values (through Multi Criteria Decision Analysis, MCDA, methodologies). The application to a Polish case-study shows the performance and the flexibility of the system in investigating and mapping (potentially) contaminated sites at the regional scale.

Regional risk assessment for contaminated sites part 1: vulnerability assessment by multicriteria decision analysis

As highlighted in the EU Soil Communication, local contamination is one of the main soil threats and it is often related to present and past industrial activities which left a legacy of a high number of contaminated sites in Europe. These contaminated sites can be harmful to many different receptors according to their sensitivity/susceptibility to contamination, and specific vulnerability evaluations are needed in order to manage this widely spread environmental issue. In this paper a novel comprehensive vulnerability assessment framework to assess regional receptor susceptibility to contaminated site is presented. The developed methodology, which combines multi criteria decision analysis (MCDA) techniques and spatial analysis, can be applied to different receptors recognized as relevant for regional assessment. In order to characterize each receptor, picked parameters significant for the estimation of the vulnerability to contaminated sites have been selected, normalized and aggregated by means of multi criteria decision analysis (MCDA) techniques. The developed MCDA methodology, based on the Choquet integral, allows to include expert judgments for the elicitation of synergic and conflicting effects between involved criteria and is applied to all the geographical objects representing the identified receptors. To test the potential of the vulnerability methodology, it has been applied to a specific case study area in the upper Silesia region of Poland where it proved to be reliable and consistent with the environmental experts' expected results. The vulnerability assessment results indicate that groundwater is the most vulnerable receptor characterized by a wide area with vulnerability scores belonging to the highest vulnerability class. As far as the other receptors are concerned, human health and surface water are characterized by quite homogeneous vulnerability scores falling in the medium-high vulnerability classes, while protected areas resulted to be the less vulnerable receptor with only one protected area falling in the medium vulnerability class. The vulnerability assessment results will support the regional risk assessment for the ranking of potentially contaminated sites at regional scale.

Integrated Risk Assessment for WFD Ecological Status classification applied to Llobregat river basin (Spain). Part II - Evaluation process applied to five environmental Lines of Evidence

Many indicators and indices related to a variety of biological, physico-chemical, chemical, and hydromorphological water conditions have been recently developed or adapted by scientists in order to support water managers in the Water Framework Directive (WFD) implementation. In this context, the achievement of a comprehensive and reliable Ecological Status classification of water bodies across Europe is hampered by the lack of harmonised procedures for selecting an appropriate set of indicators and integrating heterogeneous information in a flexible way. To this purpose, an Integrated Risk Assessment (IRA)(2) methodology was developed based on the Weight of Evidence approach. This method analyses and combines a set of environmental indicators grouped into five Lines of Evidence (LoE), i.e. Biology, Chemistry, Ecotoxicology, Physico-chemistry and Hydromorphology. The whole IRA methodology has been implemented as a specific module into a freeware GIS (Geographic Information System)-based Decision Support System, named MODELKEY DSS. This paper focuses on the evaluation of the four supporting LoE (i.e. Chemistry, Ecotoxicology, Physico-chemistry and Hydromorphology), and includes a procedure for a comparison of each indicator with proper thresholds and a subsequent integration process to combine the obtained output with the LoE Biology results in order to provide a single score expressing the Ecological Status classification. The approach supports the identification of the most prominent stressors, which are responsible for the observed alterations in the river basin under investigation. The results provided by the preliminary testing of the IRA methodology through application of the MODELKEY DSS to the Llobregat case study are finally reported and discussed.

Integrated risk assessment for WFD ecological status classification applied to Llobregat river basin (Spain). Part I-Fuzzy approach to aggregate biological indicators

Water Framework Directive (WFD) requirements and recommendations for Ecological Status (ES) classification of surface water bodies do not address all issues that Member States have to face in the implementation process, such as selection of appropriate stressor-specific environmental indicators, definition of class boundaries, aggregation of heterogeneous data and information and uncertainty evaluation. In this context the "One-Out, All-Out" (OOAO) principle is the suggested approach to lead the entire classification procedure and ensure conservative results. In order to support water managers in achieving a more comprehensive and realistic evaluation of ES, an Integrated Risk Assessment (IRA) methodology was developed. It is based on the Weight of Evidence approach and implements a Fuzzy Inference System in order to hierarchically aggregate a set of environmental indicators, which are grouped into five Lines of Evidence (i.e. Biology, Chemistry, Ecotoxicology, Physico-chemistry and Hydromorphology). The whole IRA methodology has been implemented as an individual module into a freeware GIS (Geographic Information System)-based Decision Support System (DSS), named MODELKEY DSS. The paper focuses on the conceptual and mathematical procedure underlying the evaluation of the most complex Line of Evidence, i.e. Biology, which identifies the biological communities that are potentially at risk and the stressors that are most likely responsible for the observed alterations. The results obtained from testing the procedure through application of the MODELKEY DSS to the Llobregat case study are reported and discussed.